Applied AI Engineer

What You’ll Do

• Architect and develop enterprise-grade conversational AI solutions for leadership coaching
• Develop, design and implement improvements in user experience in conversational interactions leveraging LLMs in novel ways to advance product goals.
• Evaluate and improve existing conversational (LLM-based) models across dimensions of  effectiveness, scalability, and efficiency. 
• Implement, test, and deploy LLM-powered coaching agents that understand complex tasks, provide accurate and relevant responses, and adapt to diverse conversational contexts
• Integrate and manage diverse data sources to enhance the knowledge and contextual understanding of our AI coaching models
• Work with the product team to study user behavior and prioritize evolving product developments.
• Experiment at a high velocity to optimize user experience 
• Full stack - write, review and deploy code across back and front end as needed
• Streamlining data science processes to support rapid iteration and quality improvement. 
• Support other science and software development where required.

What We’re Looking For

• Bachelor’s degree in Computer Science, Engineering, Mathematics, related field, or equivalent experience
• 3+ years of professional experience (or equivalent) in software engineering, AI/ML development (ideally including a Master’s or Ph.D. in Computer Science, ML, Data Science, or a related field)
• Practical and theoretical knowledge of language systems in the areas of: conversational systems, NLP, and Information Retrieval with knowledge of relevant tools
• Strong software engineering skills with a track record of developing data-driven machine learning systems or products
• Proficiency in Python and relevant deep learning frameworks - both training (e.g. PyTorch, Tensorflow, JAX) and serving (e.g., Hugging Face TGI/Transformers/Adapters/outlines, vLLM)
• Experience with cloud deployment of ML systems (e.g., AWS, GCP, Azure) including and open systems (e.g. Docker and Kubernetes) and their associated ML services.
• Experience with Data Science tools and processes (e.g. NumPy, scikit-learn, Pandas, PySpark)
• Familiarity with ML lifecycle tools like MLflow, Weights & Biases
• Hands-on experience building Generative AI-powered applications, including Large Language Models
• Strong analytical and problem-solving skills
• Ability to communicate complex ideas and concepts effectively
• Exposure to early-stage startups, preferably B2B SaaS

What You’ll Get

• Ownership of projects and strategic priorities regardless of seniority in our learning-focused environment.
• Strong ties to the executive team, a culture of transparency and engagement with strategic decisions.
• Options from day one, which means you will be on the ownership track right away.
• Competitive salary and equity packages.
• Comprehensive health coverage (medical, dental, and vision) from day 1.
• Provision of anything you need to be successful -  learning tools, hardware, office equipment, software.
• 401k optionality for US based employees
• Generous PTO, company-wide R&R shutdowns and paid leave for parents. 
• A WFH stipend, phone stipend and support to work in a We Work or other space as preferred.